Feasibility of a Knowledge Translation CME Program: Courriels Cochrane
Bibliographic record
Abstract
INTRODUCTION: Systematic literature reviews provide best evidence, but are underused by clinicians. Thus, integrating Cochrane reviews into continuing medical education (CME) is challenging. We designed a pilot CME program where summaries of Cochrane reviews (Courriels Cochrane) were disseminated by e-mail. Program participants automatically received CME credit for each Courriel Cochrane they rated. The feasibility of this program is reported (delivery, participation, and participant evaluation). METHOD: We recruited French-speaking physicians through the Canadian Medical Association. Program delivery and participation were documented. Participants rated the informational value of Courriels Cochrane using the Information Assessment Method (IAM), which documented their reflective learning (relevance, cognitive impact, use for a patient, expected health benefits). IAM responses were aggregated and analyzed. RESULTS: The program was delivered as planned. Thirty Courriels Cochrane were delivered to 985 physicians, and 127 (12.9%) completed at least one IAM questionnaire. Out of 1109 Courriels Cochrane ratings, 973 (87.7%) conta-ined 1 or more types of positive cognitive impact, while 835 (75.3%) were clinically relevant. Participants reported the use of information for a patient and expected health benefits in 595 (53.7%) and 569 (51.3%) ratings, respectively. DISCUSSION: Program delivery required partnering with 5 organizations. Participants valued Courriels Cochrane. IAM ratings documented their reflective learning. The aggregation of IAM ratings documented 3 levels of CME outcomes: participation, learning, and performance. This evaluation study demonstrates the feasibility of the Courriels Cochrane as an approach to further disseminate Cochrane systematic literature reviews to clinicians and document self-reported knowledge translation associated with Cochrane reviews.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.036 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.043 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".